Abstract. Natural (e.g., earthquake, flood, wildfires) and human-made (e.g., terrorism, civil strife) disasters are inevitable, can cause extensive disruption, and produce chronic and disabling psychological injuries leading to formal diagnoses (e.g., post-traumatic stress disorder [PTSD]). Following natural disasters of earthquake (Christchurch, Aotearoa/New Zealand, 2010–11) and flood (Calgary, Canada, 2013), controlled research showed statistically and clinically significant reductions in psychological distress for survivors who consumed minerals and vitamins (micronutrients) in the following months. Following a mass shooting in Christchurch (March 15, 2019), where a gunman entered mosques during Friday prayers and killed and injured many people, micronutrients were offered to survivors as a clinical service based on translational science principles and adapted to be culturally appropriate. In this first translational science study in the area of nutrition and disasters, clinical results were reported for 24 clients who completed the Impact of Event Scale – Revised (IES-R), the Depression Anxiety Stress Scales (DASS), and the Modified-Clinical Global Impression (M-CGI-I). The findings clearly replicated prior controlled research. The IES-R Cohen’s d ESs were 1.1 (earthquake), 1.2 (flood), and 1.13 (massacre). Effect sizes (ESs) for the DASS subscales were also consistently positive across all three events. The M-CGI-I identified 58% of the survivors as “responders” (i.e., self-reported as “much” to “very much” improved), in line with those reported in the earthquake (42%) and flood (57%) randomized controlled trials, and PTSD risk reduced from 75% to 17%. Given ease of use and large ESs, this evidence supports the routine use of micronutrients by disaster survivors as part of governmental response.
Supplemental energy dissipation devices are increasingly used to protect structures, limit loads transferred to structural elements and absorbing significant response energy without sacrificial structural damage. Lead extrusion dampers are supplemental energy dissipation devices, where recent development of smaller volumetric size with high force capacities, called high force to volume (HF2V) devices, has seen deployment in a large series of scaled and full-scaled experiments, as well as in three new structures in Christchurch, NZ and San Francisco, USA. HF2V devices have previously been designed using limited precision models, so there is variation in force prediction capability. Further, while the overall resistive force is predicted, the knowledge of the relative contributions of the different internal reaction mechanisms to these overall resistive forces is lacking, limiting insight and predictive accuracy in device design. There is thus a major need for detailed design models to better understand force generation, and to aid precision device design. These outcomes would speed the overall design and implementation process for uptake and use, reducing the need for iterative experimental testing. Design parameters from 17 experimental HF2V device tests are used to create finite element models using ABAQUS. The analysis is run using ABAQUS Explicit, in multiple step times of 1 second with automatic increments, to balance higher accuracy and computational time. The output is obtained from the time- history output of the contact pressure forces including the normal and friction forces on the lead along the shaft. These values are used to calculate the resistive force on the shaft as it moves through the lead, and thus the device force. Results of these highly nonlinear, high strain analyses are compared to experimental device force results. Model errors compared to experimental results for all 17 devices ranged from 0% to 20% with a mean absolute error of 6.4%, indicating most errors were small. In particular, the standard error in manufacturing is SE = ±14%. In this case, 15 of 17 devices (88%) are within ±1SE (±14%) and 2 of 17 devices (12%) are within ±2SE (±28). These results show low errors and a distribution of errors compared to experimental results that are within experimental device construction variability. The overall modelling methodology is objective and repeatable, and thus generalizable. The exact same modelling approach is applied to all devices with only the device geometry changing. The results validate the overall approach with relatively low error, providing a general modelling methodology for accurate design of HF2V devices.
